new

pipeline/kiss3d_wrapper.py

@@ -70,21 +70,22 @@ def init_wrapper_from_config(config_path):
     flux_lora_pth = hf_hub_download(repo_id="LTT/Kiss3DGen", filename="rgb_normal_large.safetensors", repo_type="model", token=access_token)
     flux_redux_pth = config_['flux'].get('redux', None)
     
-    if flux_base_model_pth.endswith('safetensors'):
-        flux_pipe = FluxImg2ImgPipeline.from_single_file(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
-    else:
-        flux_pipe = FluxImg2ImgPipeline.from_pretrained(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
+    # if flux_base_model_pth.endswith('safetensors'):
+    #     flux_pipe = FluxImg2ImgPipeline.from_single_file(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
+    # else:
+    #     flux_pipe = FluxImg2ImgPipeline.from_pretrained(flux_base_model_pth, torch_dtype=dtype_[flux_dtype], token=access_token)
     
     # load flux model and controlnet
     if flux_controlnet_pth is not None and False:
         flux_controlnet = FluxControlNetModel.from_pretrained(flux_controlnet_pth, torch_dtype=torch.bfloat16)
         flux_pipe = convert_flux_pipeline(flux_pipe, FluxControlNetImg2ImgPipeline, controlnet=[flux_controlnet])
 
-    flux_pipe.scheduler = FlowMatchHeunDiscreteScheduler.from_config(flux_pipe.scheduler.config)
+    # flux_pipe.scheduler = FlowMatchHeunDiscreteScheduler.from_config(flux_pipe.scheduler.config)
         
     # load lora weights
-    flux_pipe.load_lora_weights(flux_lora_pth)
-    flux_pipe.to(device=flux_device)
+    # flux_pipe.load_lora_weights(flux_lora_pth)
+    # flux_pipe.to(device=flux_device)
+    flux_pipe = None
 
     # load redux model
     flux_redux_pipe = None